Molecular Communication (MC) is a promising micro-scale technology that enables wireless connectivity in electromagnetically challenged conditions. The signal processing approaches in MC are different from conventional wireless communications as molecular signals suffer from severe inter-symbol interference (ISI) and signal-dependent counting noise due to the stochastic diffusion process of the information molecules. One of the main challenges in MC is the high computational complexity of the existing time-domain ISI mitigation schemes that display a third-order polynomial or even exponential growth with the ISI length, which is further exasperated under the high symbol rate case. For the first time, we develop a frequency-domain equalization (FDE) with lower complexity, capable of achieving independence from the ISI effects. This innovation is grounded in our characterization of the channel frequency response of diffusion signals, facilitating the design of receiver sampling strategies. However, the perfect counting noise power is unavailable in the optimal minimum mean square error (MMSE) equalizer. We address this issue by exploiting the statistical information of the transmit signal and decision feedback for noise power estimation, designing novel MMSE equalizers with low complexity. The FDE for MC is successfully developed with its immunity to ISI effects, and its signal processing cost has only a logarithmic growth with symbol length in each block.

中文翻译：

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分子通信的频域分析和均衡


分子通信 (MC) 是一种很有前景的微型技术，可在电磁挑战条件下实现无线连接。 MC中的信号处理方法与传统的无线通信不同，因为分子信号由于信息分子的随机扩散过程而遭受严重的符号间干扰（ISI）和信号相关的计数噪声。 MC 的主要挑战之一是现有时域 ISI 缓解方案的高计算复杂度，这些方案随着 ISI 长度呈现三阶多项式甚至指数增长，这在高符号率情况下会进一步加剧。我们首次开发了一种复杂度较低的频域均衡（FDE），能够实现不受 ISI 影响的影响。这项创新基于我们对扩散信号的通道频率响应的表征，有助于接收机采样策略的设计。然而，在最佳最小均方误差（MMSE）均衡器中无法获得完美的计数噪声功率。我们通过利用发射信号的统计信息和噪声功率估计的决策反馈来解决这个问题，设计复杂度较低的新型 MMSE 均衡器。 MC的FDE开发成功，具有抗ISI效应，其信号处理成本仅随每个块中的符号长度呈对数增长。